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MortalityPredictionEICU Task

Source: R/Task_MortalityPredictionEICU.R
MortalityPredictionEICU.Rd

Task for predicting ICU mortality using eICU-CRD dataset. Predicts whether a patient will die during the ICU stay based on clinical information collected during the stay.

Details

This task uses the unit discharge status from the patient table to determine mortality. The prediction is based on clinical codes from diagnosis, physicalExam (procedures), and medication tables.

Label definition:

  • Label = 1 if unitdischargestatus == "Expired"

  • Label = 0 otherwise

The task excludes:

  • ICU stays without any clinical codes (conditions, procedures, or drugs)

Features:

  • conditions: ICD-9 codes from diagnosis table

  • procedures: Physical examination paths from physicalexam table

  • drugs: Drug names from medication table

Super class

RHealth::BaseTask -> MortalityPredictionEICU

Public fields

task_name

Name of the task.

input_schema

Input schema.

output_schema

Output schema.

Methods

Public methods

Method new()

Initialize the task.

Usage

MortalityPredictionEICU$new()

Method pre_filter()

Pre-filter hook to retain only necessary columns.

Usage

MortalityPredictionEICU$pre_filter(df)

Arguments

df

A lazy query containing all events.

Returns

A filtered LazyFrame.

Method call()

Process a single patient (ICU stay) to generate samples.

Usage

MortalityPredictionEICU$call(patient)

Arguments

patient

A Patient object representing a single ICU stay.

Returns

A list of samples (typically one sample per ICU stay).

Method clone()

The objects of this class are cloneable with this method.

Usage

MortalityPredictionEICU$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if (FALSE) { # \dontrun{
library(RHealth)

# Load eICU dataset
eicu_ds <- eICUDataset$new(
  root = "/path/to/eicu-crd/2.0",
  tables = c("diagnosis", "medication", "physicalexam"),
  dev = TRUE
)

# Set mortality prediction task
task <- MortalityPredictionEICU$new()
sample_ds <- eicu_ds$set_task(task = task)

# View samples
head(sample_ds$samples)
} # }